Field of the Invention
One or more embodiments setting forth the ideas described throughout this disclosure pertain to the field of sporting equipment fitting. One or more embodiments present information associated with an optimally fitting piece of sporting equipment, for example the best performing piece of equipment associated with a group of second users within a range or correlation of size, range of motion or speed or any combination thereof, with respect to the user. For example, embodiments may present information related to a particular make, model, dimension, weight, length, stiffness, or other parameter associated with a piece of sporting equipment through use of a motion capture sensor to measure a user's various dimensions or sizes, range of motion and speed and/or acceleration for example. Embodiments for example prompt for and accept movement to determine distance and/or speed between two locations and/or through a rotation. For example embodiments may be utilized to determine height, arm length, wrist to floor distance, hand size, longest finger size, arm length, leg length torso length, range of motion, such as but not limited to flexion, extension, abduction, adduction, outward rotation, inward rotation, pronation, supination, inversion and eversion, and speed through any motion or rotation. The distance, range of motion and speed may be obtained for any limb or through motion of any joint or portion of the human body for example. Embodiments may further utilize the same sensor for example after coupling the sensor to the piece of equipment, to obtain motion capture data from the piece of equipment, such as speed of the equipment when moved through a typical type of motion for the piece of equipment, for example to further optimize the fit. The fit may be optimized by data mining or otherwise through calculation of a correlation of dimensions, range of motion, for example static-active, static-passive and/or dynamic/kinetic range of motion, speed/acceleration, etc., with various other users, whether alive or historical as calculated through visual or other methods. Embodiments thus determine the best performing equipment for that particular type of user, i.e., within a range of size, range of motion, speed, for example the make/model of the longest hitting, most accurate, maximum or minimum scoring, etc., as previously obtained and/or determined from or based on other users having the closest dimensions, range of motion and speed. Embodiments also enable purchasing of the equipment via the mobile device, whether the piece of equipment is shown on television or other broadcast or based on the user's previous performance data or current performance data. Embodiments may further be configured to predict a first derivative or other derivate based on age or growth rates to determine the best fitting equipment for children that will fit for the longest time or otherwise minimize costs and maximize usage of equipment as well. Other embodiments of the invention may suggest exercises and/or stretches that would improve performance to a predicted performance level based on other users performance data and suggest equipment that would be appropriate for an increase strength or flexibility so that users can “grow into” or “improve into” equipment. In addition, other embodiments of the invention may be utilized over time to detect tight areas or areas that may be indicative of injury for example and alert the user. One or more embodiments of the invention may be utilized for gait analysis for fitting of shoes.
Description of the Related Art
There are no known systems that use a given motion capture sensor to measure a user's size, range of motion, speed and then utilize that same sensor to capture motion data from a piece of sporting equipment, for example to further optimize the fit of a particular piece of sporting equipment or to gather performance data over time from the same sensor. Existing sporting equipment fitting systems are generally based on size measurements of a user. These systems generally do not take into account the range of motion or direct measurements of speed through the range of motion of various joints of a user to optimize a fit for a piece of sporting equipment. There are no known fitting systems based on motion capture data obtained from high resolution sensors, for example that include use of previously stored high resolution motion data from the user or other users or piece of equipment, or from motion capture data obtained through the analysis of historical videos for example. Known systems do not contemplate data mining of motion data and size, range of motion, speed and age of other users to maximize the performance of the user.
In addition, known systems do not provide a sensor and “app” that may be inexpensively obtained and utilized on a ubiquitous mobile device such as a mobile telephone to prompt for and obtain distance, dimensions, range of motion, speed or other measurement data and suggest optimal equipment and enable the user to immediately purchase the optimally fitting equipment from the same mobile device.
Specifically, most motion capture systems are generally utilized to observe and/or teach effective body mechanics and utilize video recording of an athlete and analysis of the recorded video of an athlete. This technique has various limitations including inaccurate and inconsistent subjective analysis based on video for example. Another technique includes motion analysis, for example using at least two cameras to capture three-dimensional points of movement associated with an athlete. Known implementations utilize a stationary multi-camera system that is not portable and thus cannot be utilized outside of the environment where the system is installed, for example during an athletic event such as a golf tournament. These fixed installations are extremely expensive as well. Such prior techniques are summarized in U.S. Pat. No. 7,264,554, filed 26 Jan. 2006, which claims the benefit of U.S. Provisional Patent Application Ser. No. 60/647,751 filed 26 Jan. 2005, the specifications of which are both hereby incorporated herein by reference. Both disclosures are to the same inventor of the subject matter of the instant application. Regardless of the motion capture data obtained, the data is generally analyzed on a per user or per swing basis that does not contemplate processing on a mobile phone, so that a user would only buy a motion capture sensor and an “app” for a pre-existing mobile phone. In addition, existing solutions do not contemplate mobile use, analysis and messaging and/or comparison to or use of previously stored motion capture data from the user or other users or data mining of large data sets of motion capture data, for example to obtain or create motion capture data associated with a group of users, for example professional golfers, tennis players, baseball players or players of any other sport to provide a “professional level” average or exceptional virtual reality opponent. To summarize, motion capture data is generally used for immediate monitoring or sports performance feedback and generally has had limited and/or primitive use in other fields. Any uses for the data with respect to fitting are limited, and generally based on the size of the user and do not utilize a given sensor to measure the user's size, range of motion and speed as well as the motion of the piece of equipment, for example after coupling the motion capture sensor to the piece of equipment after the uncoupled sensor is utilized in measuring physical parameters of the user without the piece of equipment.
Known motion capture systems generally utilize several passive or active markers or several sensors. There are no known systems that utilize as little as one visual marker or sensor and an app that for example executes on a mobile device that a user already owns, to analyze and display motion capture data associated with a user and/or piece of equipment. The data is generally analyzed in a laboratory on a per user or per swing basis and is not used for any other purpose besides motion analysis or representation of motion of that particular user and is generally not subjected to data mining. This also makes fitting for sporting equipment more difficult for the user, since the user must travel to a particular installation for custom fitting for example.
There are no known systems that allow for motion capture elements such as wireless sensors to seamlessly integrate or otherwise couple with a user or shoes, gloves, shirts, pants, belts, or other equipment, such as a baseball bat, tennis racquet or golf club for local analysis or later analysis in such a small format that the user is not aware that the sensors are located in or on these items. There are no known systems that provide seamless mounts, for example in the weight port of a golf club or at the end shaft near the handle so as to provide a wireless golf club, configured to capture motion data. Data derived from existing sensors is not saved in a database for a large number of events and is not used relative to anything but the performance at which the motion capture data was acquired. In addition, known motion capture sensors are specifically designed to mount to a piece of sporting equipment in a particular manner and are not intended to measure the user's size, range of motion or speed for example without being mounted on the piece of sporting equipment.
In addition, for sports that utilize a piece of equipment and a ball, there are no known portable systems that allow the user to obtain immediate visual feedback regarding ball flight distance, swing speed, swing efficiency of the piece of equipment or how centered an impact of the ball is, i.e., where on piece of equipment the collision of the ball has taken place. These systems do not allow for user's to play games with the motion capture data acquired from other users, or historical players, or from their own previous performances. Known systems do not allow for data mining motion capture data from a large number of swings to suggest or allow the searching for better or optimal equipment to match a user's motion capture data and do not enable original equipment manufacturers (OEMs) to make business decisions, e.g., improve their products, compare their products to other manufacturers, up-sell products or contact users that may purchase different or more profitable products.
In addition, there are no known systems that utilize motion capture data mining for equipment fitting and subsequent point-of-sale decision making for instantaneous purchasing of equipment that fits an athlete. Furthermore, no known systems allow for custom order fulfillment such as assemble-to-order (ATO) for custom order fulfillment of sporting equipment, for example equipment that is built to customer specifications based on motion capture data mining, and shipped to the customer to complete the point of sales process, for example during play or virtual reality play or for example during a television broadcast.
There are no known systems that enable data mining for a large number of users related to their motion or motion of associated equipment to find patterns in the data that allows for business strategies to be determined based on heretofore undiscovered patterns related to motion. There are no known systems that enable obtain payment from OEMs, medical professionals, gaming companies or other end users to allow data mining of motion data. For at least the limitations described above there is a need for a fitting system for sporting equipment that utilizes an motion capture sensor, for example uncoupled from the piece of sporting equipment to measure a user's size, range of motion and speed and optimize a fit for a piece of sporting equipment after coupling the motion capture sensor to the piece of sporting equipment and deriving an optimized fit based on current and/or previously stored or calculated motion data from the same user or other user's that maximally correlate with the user's size, range of motion, speed or any other parameters such as age.